ABSTRACT
The era of big data constantly introduces promising profits for the healthcare industry, but simultaneously raises challenging problems in data processing and management. The flood of automated systems in our smart cities generates large volumes of data to be integrated for valuable information which can also be applied to support in the healthcare context. Medical databases offer the capabilities to address these issues and integrate, manage and analyze the data for gaining deep insights. Especially modern graph databases support the discovery of complex relationships in ever-growing networks of heterogenous medical data. However, traditional relational databases are usually not capable of representing data networks in tables or revealing such relationships, but are still widely used as data management systems. This chapter discusses a methodology for transferring a relational to a graph database by mapping the relational schema to a graph schema. To this end, a relational schema graph is constructed for the relational database and transformed in multiple steps. The approach is demonstrated for the example of a graph-based medical information system using a dashboard on top of a Neo4j database system to visualize, explore and analyse the stored data.
